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Anim Biosci > Volume 30(7); 2017 > Article
Na, Li, and Lee: Effects of dietary forage-to-concentrate ratio on nutrient digestibility and enteric methane production in growing goats (Capra hircus hircus) and Sika deer (Cervus nippon hortulorum)

Abstract

Objective

Two experiments were conducted to determine the effects of forage-to-concentrate (F:C) ratio on the nutrient digestibility and enteric methane (CH4) emission in growing goats and Sika deer.

Methods

Three male growing goats (body weight [BW] = 19.0±0.7 kg) and three male growing deer (BW = 19.3±1.2 kg) were respectively allotted to a 3×3 Latin square design with an adaptation period of 7 d and a data collection period of 3 d. Respiration-metabolism chambers were used for measuring the enteric CH4 emission. Treatments of low (25:75), moderate (50:50), and high (73:27) F:C ratios were given to both goats and Sika deer.

Results

Dry matter (DM) and organic matter (OM) digestibility decreased linearly with increasing F:C ratio in both goats and Sika deer. In both goats and Sika deer, the CH4 emissions expressed as g/d, g/kg BW0.75, % of gross energy intake, g/kg DM intake (DMI), and g/kg OM intake (OMI) decreased linearly as the F:C ratio increased, however, the CH4 emissions expressed as g/kg digested DMI and OMI were not affected by the F:C ratio. Eight equations were derived for predicting the enteric CH4 emission from goats and Sika deer. For goat, equation 1 was found to be of the highest accuracy: CH4 (g/d) = 3.36+4.71×DMI (kg/d)−0.0036×neutral detergent fiber concentrate (NDFC, g/kg)+0.01563×dry matter digestibility (DMD, g/kg)−0.0108×neutral detergent fiber digestibility (NDFD, g/kg). For Sika deer, equation 5 was found to be of the highest accuracy: CH4 (g/d) = 66.3+27.7×DMI (kg/d)−5.91×NDFC (g/kg)−7.11× DMD (g/kg)+0.0809×NDFD (g/kg).

Conclusion

Digested nutrient intake could be considered when determining the CH4 generation factor in goats and Sika deer. Finally, the enteric CH4 prediction model for goats and Sika deer were estimated.

INTRODUCTION

Methane (CH4) production by enteric fermentation in ruminants is recognized as one of the major sources of greenhouse gas emissions worldwide [1]. Besides, the enteric CH4 represents an energy loss, ranging from 2% to 12% of the gross energy intake, for an animal [2]. Generally, the enteric CH4 production by ruminants is affected by various dietary factors such as the level of intake [3], carbohydrate type [4,5], forage processing [6], fat addition [7], and ionophore addition [8]. Moreover, the forage-to-concentrate (F:C) ratio in diets affects nutrient digestibility and enteric CH4 emission in many ruminants [911]. Although cattle and buffalo produce maximum greenhouse gases, 4.4% of the total greenhouse gas emissions from the livestock sector is contributed by the goats worldwide [12]. In addition, a large number of Sika deer inhabit East Asian areas or are domesticated in some of those areas [13]. Many studies have been conducted for measuring the emission of enteric CH4 from dairy cattle, beef cattle, or sheep; however, only a few studies have been conducted for goats and Sika deer.
Mathematical models have been developed for predicting the enteric CH4 production in ruminants [3,14,15]. Although the models based on databases taken from different studies for enteric CH4 emission from goats were already developed [16], to our knowledge, the model for enteric CH4 emission from deer did not exist. Therefore, the objective of the present study was to determine the effects of the F:C ratio on the nutrient digestibility and enteric CH4 emission from growing goats and Sika deer as well as to derive the equations for CH4 production.

MATERIALS AND METHODS

Two experiments were conducted to determine the nutrient digestibility and emission of enteric CH4 and CO2 in goats (Capra hircus hircus) and Sika deer (Cervus nippon hortulorum). We performed the experimental procedures in accordance with the Institutional Animal Care and Use Committee of Konkuk University.

Animals, diets, and experimental design

Three growing male goats with initial body weight (BW) of 19.0± 0.7 kg and three growing male deer with initial BW of 19.3±1.2 kg were used. Experiments were conducted in an environmentally controlled room (20°C±3°C). Each animal was housed individually in a respiration-metabolism chamber described by Li et al [17]. Experimental diets based on 2% of initial BW (dry matter [DM] basis) were fed daily at 1100 h. Water and mineral blocks were provided at all times. Orts were removed daily and weighed at 1000 h for DM intake calculation. Fecal samples were collected everyday by using the total collection method, dried immediately, and stored at −20°C for subsequent chemical analysis. Three experimental diets were prepared for both goat and deer experiments (Table 1). The dietary treatments included low (25:75), moderate (50:50), and high (73:27) F:C ratios. The experimental design consisted of a 3×3 Latin square design with a diet adaptation period of 7 d and a data collection period of 3 days. Adaption period was according to literature reference [18,19]. The animals were weighed at the beginning of each period.

Chemical analysis

All ingredients and fecal samples were analyzed in duplicate for DM, organic matter (OM), crude protein (CP), and ether extract (EE) as described by AOAC [20]. The contents of neutral detergent fiber (NDF) were analyzed using heat stable α-amylase (Sigma A3306; Sigma Chemical Co., St. Louis, MO, USA) according to the method described by Van Soest et al [21]. Gross energy (GE) was determined using a bomb calorimeter (C5000; IKA, Staufen, Germany).

Gas production measurement

The CH4 and carbon dioxide (CO2) production were measured using a respiration-metabolism chamber system [17]. A recovery test was performed before each period using standard CH4 gas (1.67%, v/v). Inlet and outlet gases were measured by a gas flow meter (GFM57, Aalborg Instruments & Controls Inc., Orangeburg, NY, USA); a sample pump (Columbus Instruments, Columbus, OH, USA) was used to collect gas samples. The gas samples were passed through a desiccant composed of calcium sulfate (CaSO4), before the samples flew into the gas analyzer. Non-dispersive infrared gas analyzer (VA-3000; Horiba Stec Co., Kyoto, Japan) was used to analyze the CH4 and CO2 concentrates.

Statistical analysis

The data were analyzed using SAS PROC MIXED (Version 9.2; SAS Institute Inc., Cary, NC, USA). The model considered the diet as the fixed effect and both animals and periods as the random effects. Orthogonal contrasts for linear and quadratic effects were performed with polynomials determined by SAS PROC IML (Version 9.2; SAS Institute Inc., USA). All data were presented as the least squares means. Treatment effects were considered significant at p<0.05, and trends were considered at 0.05≤p<0.10. The SAS PROC REG (Version 9.2; SAS Institute Inc., USA) was used for estimating the simple and multiple linear equations. Equations were evaluated on the basis of root mean square error (RMSE), adjusted-R2, and p-value.

RESULTS AND DISCUSSION

The DM and OM digestibility of goats decreased linearly (p<0.01) as the F:C ratio increased (Table 2). The DM, OM, and CP digestibility of Sika deer also decreased linearly (p<0.01) as the F:C ratio increased. An increase in the F:C ratio decreases the DM and OM digestibility for other ruminants, such as a cow [22] and sheep [23,24], because the forage has a generally higher NDF content than the concentrate. As structural carbohydrates (e.g. NDF) are usually less digestible than non-fiber carbohydrates, the total digestibility decreases with increasing proportions of forage in the diet [4]. In agreement with previously reported results in other studies on goats [25,26] or deer [27], in the present study, the DM and OM digestibility decreased (p<0.01) with increasing F:C ratios. As the NDF digestibility of goats and Sika deer were not significantly affected by the F:C ratios, their DM digestibility decreased with increasing F:C ratios.
In goats and Sika deer, the enteric emission of CH4 expressed as g/d, g/kg BW0.75, % of gross energy intake (GEI), g/kg DMI, and g/kg OMI decreased linearly (p<0.05) with increasing F:C ratios (Table 3). However, no difference was observed in enteric CH4 production expressed as g/kg digested dry matter intake (DDMI) and g/kg digested organic matter intake (DOMI) in both goats and Sika deer. In goats, the CO2 production expressed as g/kg BW0.75 decreased linearly (p<0.05) with increasing F:C ratio, and there was a tendency (p = 0.078) for a decrease in the CO2 production expressed as g/d. The emission of enteric CO2 by Sika deer decreased linearly (p<0.05) as the F:C ratio increased. In contrast with the current results of the goats and Sika deer, the high forage diets generally increased the CH4 production in beef [11] and dairy [9,28] cattle as well as in the modeling [14,15] and batch culture [29] studies. Structural carbohydrate-rich diet causes greater production of enteric CH4 than non-fiber carbohydrate-rich diet in dairy cows [4] because the diet containing large amounts of non-fiber carbohydrates derives propionate production in the rumen, thereby inhibiting rumen methanogen growth [30]. However, some studies for goats showed that the dietary F:C ratio did not affect CH4 (g/d) emission [10,31]. According to the morphophysiological classification of Hofmann [32], goats and Sika deer were intermediate type and concentrate eaters, respectively, whereas cattle and sheep were grass/roughage eaters. As the stomach of concentrate eaters or intermediate types has a lesser capacity, larger opening, faster passage rate, and shorter retention time than grass/roughage eaters [32], more indigested forage contents in the rumino-reticulum pass toward the omasum in concentrate eaters or intermediate types than in grass/roughage eaters. In the current study, the NDF digestibility (NDFD) was similar among the treatments in both goats (p = 0.726) and Sika deer (p = 0.278), whereas the DM digestibility showed a significant difference (p<0.001). For this difference, the low F:C ratio diet may generate more enteric CH4 than the high F:C ratio diet in goats and Sika deer because large amount of energy sources for rumen microbes was available in the low F:C ratio diet than the high F:C ratio diet. It has been widely recognized that the diversity of rumen bacteria community could vary with animal species [33] or geographical region of host animal [34]. As the enteric CH4 production is correlated with rumen microbial community structure [35], these results which comparing to bovine may be explained by rumen bacteria diversity. In addition, the restriction of experimental diets (2% of initial BW) might affect the energy balance of microorganisms in rumen. Interestingly, the results showed that in both goats and deer, the enteric CH4 production expressed as g/kg DDMI and g/kg DOMI was not affected by the F:C ratio. Although several studies [36,37] suggested that the nutrient digestibility did not related to enteric CH4 production, in general, the nutrient digestibility could play an important role in the enteric CH4 production of ruminants [38]. Therefore, digested nutrient intake, which was available for digestion by rumen microorganisms, could be considered when determining the CH4 generation factor in goats and Sika deer.
For goats, equation 1, which used the DMI, NDF concentrate (NDFC), DM digestibility (DMD), and NDFD as independent variables, showed the highest accuracy (Table 4; R2 = 0.85, RMSE = 0.74, and p = 0.059). For Sika deer, equation 5, which used the DMI, NDFC, DMD, and NDFD as independent variables, showed the highest accuracy (R2 = 0.96, RMSE = 0.54, and p = 0.004). For goats, equation 3 that did not use the digestibility factors as variables showed low accuracy (R2 = 0.24, RMSE = 1.38, and p = 0.45), whereas, for Sika deer, equation 7 that did not use digestibility factors as variables showed a relatively high accuracy (R2 = 0.88, RMSE = 0.54, and p = 0.001). The digestibility factors are usually more difficult to measure than the DMI and nutrient concentrate. Therefore, in practice, the model composed without the digestibility is more useful. Although the extant models based on the database organized from different studies on the emission of enteric CH4 by goats have already been developed [16], to our knowledge, the model for the emission of enteric CH4 by deer was not available. Thus, although the models for deer were organized from the limited database, these models will partially help to estimate the enteric CH4 emission from Sika deer.

CONCLUSION

In goats and Sika deer, the F:C ratio decreases the nutrient digestibility and the enteric CH4 emissions expressed as g/d, g/kg BW0.75, % of GEI, g/kg DMI, and g/kg OMI; however, the enteric CH4 emissions expressed as g/kg DDMI and g/kg DOMI were not affected. Therefore, digested nutrient intake, which was available for digestion by rumen microorganisms, could be considered when determining the CH4 generation factor in goats and Sika deer. In addition, as the model for enteric CH4 emission from Sika deer did not exist, the equations that were derived in this study will partially help to estimate the enteric CH4 emission from Sika deer.

Notes

CONFLICT OF INTEREST

We certify that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript.

ACKNOWLEDGMENTS

This paper was supported by Konkuk University in 2014.

Table 1
Ingredients and nutrient composition of experiment diets
Items Forage to concentrate ratio

25:75 50:50 73:27
Ingredients (%, DM basis)
 Ground corn 53.3 25.5 -
 Soybean meal 21.7 24.5 27.0
 Tall fescue, hay 25.0 50.0 73.0
Nutrient composition
 DM (%) 90.6 89.2 87.8
 OM (% DM) 93.5 92.8 92.2
 CP (% DM) 17.0 17.0 17.0
 NDF (% DM) 26.7 42.8 57.7
 GE (MJ/kg DM) 18.7 18.7 18.7

DM, dry matter; OM, organic matter; CP, crude protein; NDF, neutral detergent fiber; GE, gross energy.

Table 2
Effect of forage to concentrate ratio on nutrient digestibility in goats (Capra hircus hircus) and Sika deer (Cervus nippon hortulorum)
Digestibility (%) Forage to concentrate ratio SEM p-value


25:75 50:50 73:27 Linear Quadratic
Goats
 DM 78.1 68.0 58.5 2.0 <0.001 0.983
 OM 79.8 69.0 58.6 2.0 0.002 0.954
 CP 80.5 78.6 77.2 2.1 0.308 0.948
 NDF 47.1 45.8 45.5 3.4 0.726 0.906
Sika deer
 DM 76.9 63.8 54.5 0.8 <0.001 0.194
 OM 78.2 64.7 55.0 0.8 <0.001 0.212
 CP 76.8 73.2 72.2 1.3 0.028 0.368
 NDF 44.1 38.2 40.1 2.5 0.278 0.253

SEM, standard error of the mean; DM, dry matter; OM, organic matter; CP, crude protein; NDF, neutral detergent fiber.

Table 3
Effect of forage to concentrate ratio on enteric methane and carbon dioxide in goats (Capra hircus hircus) and Sika deer (Cervus nippon hortulorum)
Items Forage to concentrate ratio SEM p-value


25:75 50:50 73:27 Linear Quadratic
Goats
 CH4 production
  CH4 (g/d) 10.7 9.2 8.0 0.5 0.008 0.869
  CH4 (g/kg BW0.75) 1.2 1.0 0.9 0.1 0.034 0.977
  CH4 (% of GEI) 8.6 7.3 6.0 0.5 0.032 0.934
  CH4 (g/kg DMI) 29.1 24.6 20.2 1.7 0.032 0.934
  CH4 (g/kg DDMI) 37.1 36.4 34.5 2.7 0.474 0.828
  CH4 (g/kg OMI) 31.1 26.5 21.9 1.8 0.035 0.916
  CH4 (g/kg DOMI) 38.9 38.6 37.2 2.8 0.638 0.848
 CO2 production
  CO2 (g/d) 376 357 337 14 0.078 0.941
  CO2 (g/kg BW0.75) 42.3 39.6 36.1 1.4 0.011 0.659
Sika deer
 CH4 production
  CH4 (g/d) 10.1 9.6 7.2 1.0 0.002 0.051
  CH4 (g/kg BW0.75) 1.1 1.0 0.8 0.04 0.006 0.158
  CH4 (% of GEI) 7.8 7.2 5.7 0.3 0.002 0.162
  CH4 (g/kg DMI) 26.1 24.3 19.0 0.9 0.002 0.162
  CH4 (g/kg DDMI) 33.9 38.1 35.1 1.8 0.654 0.165
  CH4 (g/kg OMI) 27.9 26.1 20.7 1.0 0.002 0.156
  CH4 (g/kg DOMI) 35.7 40.4 37.7 1.9 0.470 0.167
 CO2 production
  CO2 (g/d) 432 403 341 24 0.003 0.212
  CO2 (g/kg BW0.75) 47.4 43.7 37.8 2.9 0.013 0.321

SEM, standard error of the mean; CH4, methane; BW, body weight; GEI, gross energy intake; DMI, dry matter intake; DDMI, digested dry matter intake; OMI, organic matter intake; DOMI, digested organic matter intake; CO2, carbon dioxide.

Table 4
Equations for enteric methane emission from goats (Capra hircus hircus) and Sika deer (Cervus nippon hortulorum)
Items Equations Statistical parameters

R2 RMSE p-value
Goats
 1 CH4 (g/d) = 3.36(±5.96)+4.71(±14.1)×DMI (kg/d)−0.0036(±0.0021)×NDFC (g/kg)+0.01563(±0.0040) ×DMD (g/kg)−0.0108(±0.0070)×NDFD (g/kg) 0.85 0.74 0.059
 2 CH4 (g/d) = 4.81(±6.67)−6.66(±13.7)×DMI (kg/d)−0.0027(±0.0022)×NDFC (g/kg)+0.0119(±0.0036) ×DMD (g/kg) 0.76 0.84 0.051
 3 CH4 (g/d) = 19.6(±8.16)−23.7(±20.8)×DMI (kg/d)−0.0030(±0.0037)×NDFC (g/kg) 0.24 1.38 0.445
 4 CH4 (g/d) = 17.8(±7.71)−22.45(±20.2)×DMI (kg/d) 0.15 1.35 0.304
Sika deer
 5 CH4 (g/d) = 66.3(±24.6)+27.7(±4.48)×DMI (kg/d)−5.91(±2.12)×NDFC (g/kg)−7.11(±3.07)×DMD (g/kg) +0.0809(±0.0888)×NDFD (g/kg) 0.96 0.54 0.004
 6 CH4 (g/d) = 48.3(±14.4)+24.8(±3.09)×DMI (kg/d)−4.30(±1.14)×NDFC (g/kg)−4.73(±1.56)×DMD (g/kg) 0.95 0.53 0.001
 7 CH4 (g/d) = 4.81(±1.91)+20.3(±4.18)×DMI (kg/d)−0.882(±0.216)×NDFC (g/kg) 0.88 0.82 0.002
 8 CH4 (g/d) = 0.820(±2.95)+21.0(±7.51)×DMI (kg/d) 0.53 1.48 0.027

RMSE, root mean square error; CH4, methane; DMI, dry matter intake; NDFC, neutral detergent fiber concentrate; DMD, dry matter digestibility; NDFD, neutral detergent fiber digestibility.

REFERENCES

1. IPCC. Intergovernmental Panel on Climate Change. 2006 IPCC guidelines for national greenhouse gas inventories. Intergovernmental Panel on Climate Change; 2006.

2. Johnson KA, Johnson DE. Methane emissions from cattle. J Anim Sci 1995; 73:2483–92.
crossref pmid
3. Blaxter KL, Clapperton JL. Prediction of the amount of methane produced by ruminants. Br J Nutr 1965; 19:511–22.
crossref pmid
4. Moe PW, Tyrrell HF. Methane production in dairy cows. J Dairy Sci 1979; 62:1583–6.
crossref
5. Philippeau C, Lettat A, Martin C, et al. Effects of bacterial direct-fed microbials on ruminal characteristics, methane emission, and milk fatty acid composition in cows fed high-or low-starch diets. J Dairy Sci 2017; 100:2637–50.
crossref pmid
6. Okine EK, Mathison GW, Hardin RT. Effects of changes in frequency of reticular contractions on fluid and particulate passage rates in cattle. J Anim Sci 1989; 67:3388–96.
crossref pmid
7. Jeong C-D, Mamuad LL, Kim S-H, et al. Effect of soybean meal and soluble starch on biogenic amine production and microbial diversity using in vitro rumen fermentation. Asian-Australas J Anim Sci 2015; 28:50–7.
crossref pmid pmc pdf
8. Goodrich RD, Garrett JE, Gast DR, et al. Influence of monensin on the performance of cattle. J Anim Sci 1984; 58:1484–98.
crossref pmid
9. Aguerre MJ, Wattiaux MA, Powell JM, Broderick GA, Arndt C. Effect of forage-to-concentrate ratio in dairy cow diets on emission of methane, carbon dioxide, and ammonia, lactation performance, and manure excretion. J Dairy Sci 2011; 94:3081–93.
crossref pmid
10. Islam M, Abe H, Hayashi Y, Terada F. Effects of feeding Italian ryegrass with corn on rumen environment, nutrient digestibility, methane emission, and energy and nitrogen utilization at two intake levels by goats. Small Rumin Res 2000; 38:165–74.
crossref
11. Lovett D, Lovell S, Stack L, et al. Effect of forage/concentrate ratio and dietary coconut oil level on methane output and performance of finishing beef heifers. Livest Prod Sci 2003; 84:135–46.
crossref
12. FAO, Food Agric Organziation. Statistical Yearbook 2013: World Food and Agriculture. Rome, Italy: FAO Food Agric Organziation UN; 2013.

13. Li ZP, Liu HL, Jin CA, et al. Differences in the methanogen population exist in Sika deer (Cervus nippon) fed different diets in China. Microb Ecol 2013; 66:879–88.
crossref pmid
14. Benchaar C, Pomar C, Chiquette J. Evaluation of dietary strategies to reduce methane production in ruminants: a modelling approach. Can J Anim Sci 2001; 81:563–74.
crossref
15. Ellis JL, Kebreab E, Odongo NE, et al. Modeling methane production from beef cattle using linear and nonlinear approaches. J Anim Sci 2009; 87:1334–45.
crossref pmid
16. Patra AK, Lalhriatpuii M. Development of statistical models for prediction of enteric methane emission from goats using nutrient composition and intake variables. Agric Ecosyst Environ 2016; 215:89–99.
crossref
17. Li DH, Kim BK, Lee SR. A respiration-metabolism chamber system for measuring gas emission and nutrient digestibility in small ruminant animals. Rev Colomb Cienc Pecu 2010; 23:444–50.

18. Omed HM. Studies of the relationships between pasture type and quality and the feed intake of grazing sheep. PhD thesis. Bangor, UK: University College of North Wales; 1986.

19. Gardinal R, Calomeni GD, Cônsolo NRB, et al. Influence of polymer-coated slow-release urea on total tract apparent digestibility, ruminal fermentation and performance of Nellore steers. Asian-Australas J Anim Sci 2017; 30:34–41.
crossref pmid pmc pdf
20. AOAC. Official methods of analysis. Assoiciation of Official Analytical Chemists. Washington, DC: AOAC International; 1995.

21. Van Soest PJ, Robertson JB, Lewis BA. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J Dairy Sci 1991; 74:3583–97.
crossref pmid
22. Yang WZ, Beauchemin KA, Rode LM. Effects of grain processing, forage to concentrate ratio, and forage particle size on rumen pH and digestion by dairy cows. J Dairy Sci 2001; 84:2203–16.
crossref pmid
23. Moss AR, Givens DI, Garnsworthy PC. The effect of supplementing grass silage with barley on digestibility, in sacco degradability, rumen fermentation and methane production in sheep at two levels of intake. Anim Feed Sci Technol 1995; 55:9–33.
crossref
24. Ramos S, Tejido ML, Martinez ME, Ranilla MJ, Carro MD. Microbial protein synthesis, ruminal digestion, microbial populations, and nitrogen balance in sheep fed diets varying in forage-to-concentrate ratio and type of forage. J Anim Sci 2009; 87:2924–34.
crossref pmid
25. Cantalapiedra-Hijar G, Yanez-Ruiz DR, Martin-Garcia AI, Molina-Alcaide E. Effects of forage:concentrate ratio and forage type on apparent digestibility, ruminal fermentation, and microbial growth in goats. J Anim Sci 2008; 87:622–31.
crossref pmid
26. Kawas JR, Lopes J, Danelon DL, Lu CD. Influence of forage-to-concentrate ratios on intake, digestibility, chewing and milk production of dairy goats. Small Rumin Res 1991; 4:11–8.
crossref
27. Ramanzin M, Bailoni L, Schiavon S. Effect of forage to concentrate ratio on comparative digestion in sheep, goats and fallow deer. Anim Sci 1997; 64:163–70.
crossref
28. Agle M, Hristov AN, Zaman S, et al. Effect of dietary concentrate on rumen fermentation, digestibility, and nitrogen losses in dairy cows. J Dairy Sci 2010; 93:4211–22.
crossref pmid
29. García-Martínez R, Ranilla MJ, Tejido ML, Carro MD. Effects of disodium fumarate on in vitro rumen microbial growth, methane production and fermentation of diets differing in their forage:concentrate ratio. Br J Nutr 2005; 94:71
crossref pmid
30. Van Kessel JAS, Russell JB. The effect of pH on ruminal methanogenesis. FEMS Microbiol Ecol 1996; 20:205–10.
crossref
31. Yang CJ, Mao SY, Long LM, Zhu WY. Effect of disodium fumarate on microbial abundance, ruminal fermentation and methane emission in goats under different forage:concentrate ratios. Animal 2012; 6:1788–94.
crossref pmid
32. Hofmann RR. Evolutionary steps of ecophysiological adaptation and diversification of ruminants: a comparative view of their digestive system. Oecologia 1989; 78:443–57.
crossref pmid
33. Jeyanathan J, Kirs M, Ronimus RS, Hoskin SO, Janssen PH. Methanogen community structure in the rumens of farmed sheep, cattle and red deer fed different diets. FEMS Microbiol Ecol 2011; 76:311–26.
crossref pmid
34. Zhou MI, Hernandez-Sanabria E, Le Luo Guan. Assessment of the microbial ecology of ruminal methanogens in cattle with different feed efficiencies. Appl Environ Microbiol 2009; 75:6524–33.
crossref pmid pmc
35. Danielsson R, Dicksved J, Sun L, et al. Methane Production in dairy cows correlates with rumen methanogenic and bacterial community structure. Front Microbiol 2017; 8:226
crossref pmid pmc
36. Ramin M, Huhtanen P. Development of equations for predicting methane emissions from ruminants. J Dairy Sci 2013; 96:2476–93.
crossref pmid
37. Stergiadis S, Zou C, Chen X, et al. Equations to predict methane emissions from cows fed at maintenance energy level in pasture-based systems. Agric Ecosyst Environ 2016; 220:8–20.
crossref
38. Negussie E, de Haas Y, Dehareng F, et al. Invited review: Large-scale indirect measurements for enteric methane emissions in dairy cattle: A review of proxies and their potential for use in management and breeding decisions. J Dairy Sci 2017; 100:2433–53.
crossref pmid


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